Biometric customer service agent analysis systems and methods

ABSTRACT

Devices, systems, and methods to receive and analyze biometric measurements from a customer service agent are provided. The analysis of the biometric measurements may be used to identify correlations between the biometric measurements, agent health, and agent performance. These correlations may then be used to route communications to the agent and/or modify the performance and/or increase the heath of the agent. The biometric measurements may also be correlated to an empathy level of the agent.

TECHNICAL FIELD

The present disclosure generally relates to devices, systems, andmethods to receive biometric measurements from an agent and identifycorrelations between the biometric measurements and performance. Thesecorrelations may then be used to route communications to the agent andincrease the performance and/or heath of the agent. The biometricmeasurements may also be correlated to an empathy level.

BACKGROUND OF THE DISCLOSURE

Customer service centers (also known as call centers) handle large loadsof communications from a variety of sources. To more effectively handlethese communications, efforts to improve efficiency often center on theperformance of customer service agents as they deal with thesecommunications. Along with other performance metrics, these efforts mayinclude collecting biometric measurements from agents during theirhandling of communications, such as blood pressure and heart rate.

However, biometric measurements are often difficult to collect during anagent's handling of communications. The collection of biometricmeasurements itself may interfere with the agents' work and decreaseperformance levels. Furthermore, the use of biometric measurements isgenerally limited to tracking basic stress levels via limitedmeasurements such as blood pressure and heart rate in existingefficiency improvement systems. Another problem with the collection ofbiometric measurements is that correlations between biometricmeasurements and agent performance are not well understood.

Furthermore, recent advances in psychophysiological studies have pointedto methods to objectively measure empathy levels of individuals. Agentswho are perceived to be “empathetic” often receive higher performancescores. However, biometric measurements are not correlated to an empathylevel in existing efficiency improvement systems.

Accordingly, needs exist to collect more types of biometric measurementsfrom agents, correlate biometric measurements to performance, and usethis correlation to increase the performance and/or health of agents.

SUMMARY

The present disclosure describes methods and systems that measure andanalyze agent biometric data. In some embodiments, a method of routing acommunication with a customer in a customer service center is provided,which includes: routing a customer communication to a customer serviceagent; receiving biometric data for the agent that is measured inassociation with the customer communication; creating a biometricanalysis based on comparing the measured biometric data to a pluralityof pre-set biometric data parameters; determining a performance scorebased on the agent's performance in interacting with the customer duringthe communication; correlating the biometric analysis to the performancescore; creating a performance recommendation for modifying performanceof the agent in one or more future communications; and providing arouting recommendation for the one or more future communications basedon the performance recommendation.

In some embodiments, the measured biometric data include one or more ofa blood pressure, a heart rate, a heart rate variability, a blood oxygenlevel, a breath rate, an electrocardiogram (EKG) reading, a skintemperature, a skin conductance, and a facial expression. The method mayalso include measuring the biometric data with a biometric measurementdevice associated with the customer service agent. In some embodiments,the biometric measurement device is configured to be worn on an arm ofthe agent.

The method may also include displaying the performance recommendation toa user. The performance recommendation may include an action to increasea health score of the agent. The method may also include correlating thebiometric data to an empathy score for the agent. The performancerecommendation may include an action to increase the empathy score ofthe agent.

In some embodiments, the method may include displaying the routingrecommendation to a user, or distributing the routing recommendation toa contact center for routing a customer to an agent during one or morefuture communications. The user may be the agent, a supervisor of theagent, or a medical practitioner, or a combination thereof.

A method for creating recommendations to beneficially modify the healthof a contact center agent is also provided, which includes: routing oneor more customer communications with a customer to the agent; receivingmeasurements of biometric data for the agent taken while the agentinteracts with the customer; creating a health recommendation tobeneficially modify an aspect of the agent's health; and displaying thehealth recommendation to a user.

The method may also include providing a routing recommendation for oneor more future communications based on the health recommendation ordetermining a health score based on the biometric data. The health scoremay include a stress level assessment, an overall health assessment, orboth. The biometric data may include one or more of a blood pressure, aheart rate, a heart rate variability, a blood oxygen level, a breathrate, an electrocardiogram (EKG) reading, a skin temperature, a skinconductance, and a facial expression.

A system to modify performance of contact center agents based onmeasured biometric attributes is also provided, which includes: abiometric measurement device including one or more biometric sensorsconfigured to measure one or more biometric attributes of a contactcenter agent; an analysis processor in communication with the biometricmeasurement device, wherein the analysis processor is operably connectedto a non-transitory computer readable medium which includes a pluralityof instructions stored in association therewith that are accessible to,and executable by, the processor, wherein the plurality of instructionswhen executed: receive the one or more biometric attributes from the oneor more biometric sensors during a communication with a customer;determine a performance score based on an agent interaction with thecustomer during the communication; correlate the performance score ofthe agent to the one or more biometric attributes; provide a performancerecommendation based on a comparison of the performance score and theone or more biometric attributes; and provide a routing recommendationfor one or more future communications for the agent based on theperformance recommendation.

In some embodiments, the system may include a display device configuredto display the performance recommendation to a user. The one or morebiometric attributes may include one or more of a blood pressure, aheart rate, a heart rate variability, a blood oxygen level, a breathrate, an electrocardiogram (EKG) reading, a skin temperature, a skinconductance, and a facial expression.

In some embodiments, the one or more biometric sensors include one ormore of a heart rate monitor, a blood oxygen monitor, a breath ratesensor, an electrodermal analysis (EDA) sensor, a thermometer, an EKGsystem, a facial recognition system, and a functional magnetic resonanceimaging (FMRI) system. The biometric measurement device may beconfigured to be worn on an arm of the agent.

In some embodiments, the plurality of instructions further include:correlating the one or more biometric attributes to an empathy score;comparing the empathy score to the performance score; and providing anempathy recommendation based on a comparison of the empathy score to theperformance score, wherein the empathy recommendation is based onincreasing the empathy score. The plurality of instructions may alsoinclude providing a routing recommendation for one or more futurecommunications based on the empathy recommendation.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is best understood from the following detaileddescription when read with the accompanying figures. It is emphasizedthat, in accordance with the standard practice in the industry, variousfeatures are not drawn to scale. In fact, the dimensions of the variousfeatures may be arbitrarily increased or reduced for clarity ofdiscussion.

FIG. 1 is a block diagram of an embodiment of an exemplary system forreceiving and analyzing communications and biometric data according tovarious aspects of the present disclosure.

FIG. 2 is a detailed block diagram of an exemplary analysis systemaccording to aspects of the present disclosure.

FIG. 3 is a detailed block diagram of an exemplary biometric measurementdevice according to aspects of the present disclosure.

FIG. 4 is a flowchart illustrating an exemplary method of routingcommunications based on biometric data according to aspects of thepresent disclosure.

FIG. 5 is a flowchart illustrating an exemplary method of increasingagent health and empathy based on biometric data according to aspects ofthe present disclosure.

DETAILED DESCRIPTION

The present disclosure advantageously describes devices, systems, andmethods to receive and analyze biometric measurements from a contactcenter agent. The analysis of the biometric measurements may be used toidentify correlations between the biometric measurements, agent health,and agent performance. These correlations may then be used to routecommunications to the agent, improve the performance and heath of theagent, or both. The biometric measurements may also be correlated to anempathy level of the agent.

For the purposes of promoting an understanding of the principles of thepresent disclosure, reference will now be made to the embodimentsillustrated in the drawings, and specific language will be used todescribe the same. It is nevertheless understood that no limitation tothe scope of the disclosure is intended. Any alterations and furthermodifications to the described devices, systems, and methods, and anyfurther application of the principles of the present disclosure arefully contemplated and included within the present disclosure as wouldnormally occur to one of ordinary skill in the art to which thedisclosure relates. In particular, it is fully contemplated that thefeatures, components, and/or steps described with respect to oneembodiment may be combined with the features, components, and/or stepsdescribed with respect to other embodiments of the present disclosure.For example, although the present disclosure refers to a customerservice agent, the devices, systems, and methods may be applied to anyuser. For the sake of brevity, however, the numerous iterations of thesecombinations will not be described separately.

FIG. 1 is a simplified block diagram of an embodiment of an analysiscenter 100 according to various aspects of the present disclosure. Ananalysis center 100 as described herein may include any facility orsystem server suitable for receiving and recording electroniccommunications from data sources. Such data sources may includecommunications on the internet, communications from customers to one ormore businesses (it being understood that customers is used herein toinclude contacts who may become future customers), and communicationsbetween employees. In some embodiments, the analysis center 100 is acustomer service center or call center. In this case, communicationsreceived by the analysis center 100 may be routed to agents based on arouting algorithm. The communications received by each agent may dependon a skill set or a work load of the agent. In some embodiments,biometric measurements of the agents of the analysis center 100 arecollected during their handling of received communications.

As shown in FIG. 1, the analysis center 100 is operable to receive andrecord varying electronic communications and data formats. In someembodiments, an intake 110 of the analysis center 100 collects data fromnumerous data sources. For example, the analysis center 100 may collectdata from telephones and cellular (i.e. mobile) phones 120, faxmachines, computers 130, or personal computing devices 150, as well asdirectly scraping information from one or more websites or otherinformation on the Internet 140. Further, the analysis center 100 mayaccept internet-based interaction sessions from computers 130, VoIPtelephones, and personal computing devices 150 such as internet-enabledsmartphones and tablets, and personal digital assistants (PDAs). Thesedata sources generally include voice and non-voice data. Other datasources may include video interactions, facsimile transmissions,e-mails, web interactions, texts, chats, and voice over IP (“VoIP”).These communications may occur on public switched telephone network(PSTN) or the Internet, e.g., including via Skype®, Facetime®, Tango™,or any other communication app, program, website, or other software orhardware. Various specific types of communications contemplated throughone or more of these channels include, without limitation, email, SMSdata (e.g., text), tweet, instant message, web-form submission,smartphone app, social media data, and web content data (including butnot limited to internet survey data, blog data, microblog data,discussion forum data, and chat data), etc. In some embodiments, thecommunications may include customer tasks, such as taking an order,making a sale, responding to a complaint, etc. It is contemplated thatthese data sources may be transmitted by and through any type oftelecommunication device and over any medium suitable for carrying suchdata. For example, the data sources may be transmitted by or throughtelephone lines, cable, or wireless communications (e.g., satellite,Wi-Fi, Bluetooth, cellular phone network, etc.).

In one preferred embodiment of this disclosure, irrespective of otherdata collected by the customer analysis center 100, a portion of thedata received is in the form of one or more customer communications witha contact center agent. In other embodiments, however, the data iscollected and stored in association with each customer, and then usedaccording to the disclosure during the current customer communicationwith the contact center agent.

In some cases, the intake 110 is configured to convert data streams withanalog data, such as audio or voice data, into a digital format. In somecases, the data streams are converted into binary or text-based forms.Furthermore, the conversion of digital data to words and terms may occurat an analysis control center 160. The digitized data may becommunicated to the cloud network 170 and the display 190.

As one of ordinary skill in the art would recognize, the communicationchannels associated with an analysis center 100 illustrated in FIG. 1are just an example, and the analysis center 100 may accept other datafrom other sources, through various additional and/or different devicesand communication channels whether or not expressly described herein.For example, in some embodiments, internet-based interactions,video-based interactions and/or telephone-based interactions may berouted through a customer service center, such as a call center orfulfillment center, before reaching the analysis center 100. It shouldbe understood that such a customer service center may includestand-alone or third-party service centers or proprietary servicecenters (e.g., staffed with employees or consultants for a particularcompany, such as a computer vendor, airline, social media app, hotelchain, etc.). These interactions may also be routed simultaneously tothe analysis center 100 and the customer service center (or evendirectly and only to the analysis center 100, in some embodiments to bedistributed to a customer service center after analysis according to thedisclosure herein). In some instances, the customer service centercaptures interaction data relevant to the analysis center 100, andapplies computer-implemented linguistic algorithms to the data togenerate digital data for the analysis center 100. In other embodiments,the analysis center 100 applies such algorithms and generates digitaldata for analysis. Further, the customer service center may be a partof, or independent of, the analysis center 100. In other embodiments,the analysis center 100 is associated with one or more customer servicecenters and provides output, e.g., the routing recommendations and/orbiometric related recommendations, to one or more of the customerservice centers to be implemented.

The analysis center 100 or associated contact center (collectivelyreferred to in various embodiments as the analysis center) may alsoinclude a biometric measurement device 180 which is operable to receivebiometric measurements from an agent. In some embodiments, the biometricmeasurement device 180 is configured to receive biometric measurementsincluding blood pressure, heart rate, heart rate variability, bloodoxygen levels, breath rate, electrocardiogram (EKG) readings, skintemperature, skin conductance, facial expressions, and othermeasurements. In some embodiments, the biometric measurement device 180includes a device worn by the agent. In particular, the biometricmeasurement device 180 may be worn on the arm, neck, or head of anagent. Preferred embodiments on the agents arm include the wrist, bicep,or hand (e.g., a finger, the palm, back of the hand). The biometricmeasurement device 180 may include electronic wrist bands such as theAngel Sensor by Seraphim Sense Ltd. Other types of biometric measurementdevices 180 may also be used by the analysis center 100, includingmedical systems configured to take EKG and functional magnetic resonanceimaging (FMRI) readings. Furthermore, cameras may be included that areconfigured to analyze the posture and facial expressions of an agent.The biometric measurements may be sent by the one or more biometricmeasurement devices to a network within the analysis control center,such as the cloud network 170. In some embodiments, the biometricmeasurements received by the biometric measurement device 180 are sentto the analysis control center 160, the cloud network 170, display 190,or to an external location such as an external database or a third partybiometric analysis center.

The cloud network 170 may be a network equipped with wirelesscommunication functionality, such as an internet or Bluetoothconnection. The cloud network 170 may utilize storage components thatmay be located at the analysis center 100 or at an external location.The cloud network 170 may facilitate the analysis of biometricmeasurements to and automatically send the analysis to the analysiscontrol center 160 or other locations.

The analysis control center 160 may be generally configured to providerecording, voice analysis, data storage, data relationship analysis,biometric measurement analysis, behavioral analysis, performanceanalysis, health analysis, and other processing functionality to theanalysis center 100. In the illustrated embodiment, the analysis controlcenter 160 is an information handling system such as a computer, server,workstation, mainframe computer, or other suitable computing device. Inother embodiments, the analysis control center 160 may be a plurality ofcommunicatively coupled computing devices coordinated to provide theabove functionality for the analysis center 100. As shown in FIG. 1, theanalysis control center 160 is configured to perform analysis of datastreams gathered by intake 110 as well as analysis of biometric signalsreceived by the one or more biometric measurement devices 180.

In some embodiments, the analysis control center 160 is operable toanalyze the biometric measurements received by the biometric measurementdevice 180, determine a performance score for the agent, and determinean empathy score for the agent. The performance score and the empathyscore may be correlated to the biometric measurements by the analysiscontrol center 160. The correlation of the various scores and biometricmeasurements may be used to provide recommendations to the agent andothers and to provide routing recommendations for routing communicationsin the analysis center 100. Biometric analysis may also be used todetermine a health level of the agent. This may help in identifyingproblems within the analysis center 100 and may be used to improve theoverall health of agents.

The analysis of the biometric measurements and creation of theperformance score, empathy score, and health level may includeperforming software instructions on received data, applying algorithmsto the data, or by sorting the data in other ways. The results of thedata are preferably communicated to the display 190, although it shouldbe understood that the data may be stored first for display later,transmitted remotely for display, etc., or both. The display 190 mayinclude an interface such as a computer screen on which a user may viewanalysis results, scores, and recommendations. The display 190 may alsobe included as an integrated component of an analysis control system 200as shown in FIG. 2.

FIG. 2 shows a block diagram of an analysis control system 200 accordingto aspects of the present disclosure. In some embodiments, the analysiscontrol system 200 may perform some or all of the functionality ascribedto the analysis control center 160 of FIG. 1. For instance, the analysiscontrol system 200 may record or receive telephone, internet, and/orother interactions or communications, perform data conversion and dataanalysis, perform other analysis center-related computing tasks, as wellas combinations thereof. In particular, the analysis control system 200may be integrated into the analysis control center 160 as a hardware orsoftware module and share its computing resources, such as with one ormore of intake 110, cloud network 170, and display 190. Alternatively,the analysis control system 200 may be a separate computing system fromthe analysis control center 160.

The analysis control system 200 may be configured to analyze biometricmeasurements and conduct automated analysis on data streams. Inparticular, the analysis control system 200 may be configured to analyzea set of biometric measurements in order to make a routingrecommendation. In some embodiments, the analysis control center 200 isoperable to compare the biometric measurements to a performance score oran empathy score of an agent. The performance score and empathy scoremay be based on the performance and empathy of the agent during his orher handling of one or more communications. The analysis control system200 may include a bus component 210, an analysis engine 220, a networkinterface component 260, a communications link 270, a storage component280, an input component 290, and a display component 292. In some cases,the analysis engine 220 is configured to analyze data streams receivedby the analysis control system 200. The analysis engine 220 may includea processor 230 that is communicatively coupled to a memory 250, as wellas a set of instructions 240.

In accordance with embodiments of the present disclosure, analysisengine 220 performs specific operations by processor 230 executing oneor more sequences of one or more instructions 240 contained in memory250. The processor 230 may be any custom made or commercially availableprocessor, a central processing unit (CPU), an auxiliary processor amongseveral processors associated with the analysis control system 200, asemiconductor-based microprocessor (in the form of a microchip or chipset), a macroprocessor, a collection of communicatively coupledprocessors, or any device for executing software instructions. Thememory 250 provides the processor 230 with non-transitory,computer-readable storage to facilitate execution of computerinstructions by the processor 230. Examples of memory 250 may includerandom access memory (RAM) devices such as dynamic RAM (DRAM),synchronous DRAM (SDRAM), solid state memory devices, and/or a varietyof other memory devices known in the art.

Logic may be encoded in a computer readable medium, which may refer toany medium that participates in providing instructions 240 to processor230 for execution. In one embodiment, the computer readable medium isnon-transitory. Such a medium may take many forms, including but notlimited to, non-volatile media, volatile media, and transmission media.In various implementations, volatile media includes dynamic memory, suchas memory 250, and transmission media includes coaxial cables, copperwire, and fiber optics, including wires that comprise bus component 210.Memory may be used to store visual representations of the differentoptions for searching or auto-synchronizing. In one example,transmission media may take the form of acoustic or light waves, such asthose generated during radio wave and infrared data communications. Somecommon forms of computer readable media include, for example, RAM, PROM,EPROM, FLASH-EPROM, any other memory chip or cartridge, carrier wave, orany other medium from which a computer is adapted to read.

Furthermore, instructions 240 may be read into memory 250 from anothercomputer readable medium, such as storage component 280. These mayinclude instructions to receive sensor data including biometricmeasurements, analyze the sensor data, receive empathy data from one ormore users, receive performance data from one or more users, compare thesensor data with the performance data and the empathy data, makerecommendations based on the comparison of sensor data and performancedata, and display the recommendations in various formats to a user. Inother embodiments, hard-wired circuitry may be used in place of or incombination with software instructions for implementation of one or moreembodiments of the disclosure.

Computer programs, instructions, and data may be stored on the storagecomponent 280. The storage component 280 may include mass storagedevices including hard discs, optical disks, magneto-optical discs,solid-state storage devices, tape drives, CD-ROM drives, and/or avariety of other mass storage devices known in the art. Further, themass storage device may be implemented across one or more network-basedstorage systems, such as a storage area network (SAN).

Still referring to FIG. 2, the interface component 260 may be operableto receive and transmit analysis center-related data between local andremote networked systems and communicate information via thecommunications link 270. Examples of interface components 260 mayinclude Ethernet cards, 802.11 WiFi devices, cellular data radios,and/or other suitable devices. The analysis control system 200 mayfurther include any number of additional components, which are omittedfor simplicity, such as input and/or output (I/O) devices (orperipherals), buses, dedicated graphics controllers, storagecontrollers, buffers (caches), and drivers. Further, functionalitydescribed in association with the analysis control system 200 may beimplemented in software (e.g., computer instructions), hardware (e.g.,discrete logic circuits, application specific integrated circuit (ASIC)gates, programmable gate arrays, field programmable gate arrays (FPGAs),etc.), or a combination of hardware and software. In some embodiments,analysis data is routed from the analysis engine 220 to an externalcommunications distributor via the interface component 260.

The display component 292 may be configured to transmit data in atextual or graphical format, such as on a computer monitor or a portablecomputing device (e.g., a cellphone, a tablet device, etc.). In somecases, analysis data from the analysis engine 220 is available to bedisplayed in several formats, optionally even simultaneously on thedisplay component 292. For example, the display component 292 may show aperformance score alongside a list of recommendations to improveperformance. Alternatively, the display component 292 is an interface toan external display.

FIG. 3 shows a block diagram of a biometric measurement device 300according to aspects of the present disclosure. In some embodiments, thebiometric measurement device 300 may perform some or all of thefunctionality ascribed to the biometric measurement device 180 shown inFIG. 1. For instance, the biometric measurement device 300 may beoperable to receive biometric measurements from a user including bloodpressure, heart rate, heart rate variability, blood oxygen levels,breathing rate, electrocardiogram (EKG) readings, skin temperature, skinconductance, facial expressions, and other measurements. In someembodiments, the biometric measurement device 300 is a single devicethat is wearable by a user. In particular, the biometric measurementdevice 300 may be configured to be worn by a customer service centeragent during work, such as on the wrist or arm of the agent. For agentsparticularly interested in their health, the biometric measurementdevice 300 may be worn all the time (except possibly during charging),may be worn during all waking hours, or used at other times outside ofwork to provide additional baseline to help ensure health is beingbeneficially modified at work through the routing recommendations and/orperformance recommendations disclosed herein. In some embodiments, theperformance of the agent may be compared with an analysis of thebiometric measurements received by the biometric measurement device 300.In other embodiments, the biometric measurement device 300 is a separatesystem from the biometric measurement device 180 and may be used inconjunction with other measurement devices.

The biometric measurement device 300 may include an analysis engine 302,a bus component 310, and, by way of a non-limiting example, a heart ratemonitor 312, a blood oxygen monitor 314, a breath rate sensor 316, anelectrodermal activity (EDA) sensor 317, or a thermometer 318, or acombination of any of the previous sensors, and a communications link320. The analysis engine 302 of the biometric measurement device 300 mayfunction similarly to the analysis engine 220 of the analysis controlsystem 200. In particular, the analysis engine 302 may be configured toreceive biometric measurements from the various sensors included withinor in communication with the biometric measurement device 300.

In accordance with embodiments of the present disclosure, analysisengine 302 performs specific operations by processor 304 executing oneor more sequences of one or more instructions 306 contained in memory308. The processor 304 may be any custom made or commercially availableprocessor. The memory 308 provides the processor 304 withnon-transitory, computer-readable storage to facilitate execution ofcomputer instructions by the processor 304. Logic may be encoded in acomputer readable medium, which may refer to any medium thatparticipates in providing instructions 306 to processor 304 forexecution. The instructions 306 may include instructions to receivesensor data from various sensors within or in communication with thebiometric measurement device 300, convert the sensor data to useableformats, and analyze the sensor data. In other embodiments, hard-wiredcircuitry may be used in place of or in combination with softwareinstructions for implementation of one or more embodiments of thedisclosure.

The bus component 310 may be configured to facilitate communicationbetween one or more components in the biometric measurement device 300.In some embodiments, the bus component 310 includes transmission mediasuch as coaxial cables, copper wire, and fiber optics.

The heart rate monitor 312 may be any commercially available or custommonitor configured to measure the heart rate of a user. In someembodiments, the heart rate monitor is configured to measure the heartrate optically, and may be disposed on a wrist band or other wearabledevice.

The blood oxygen monitor 314 may be used to measure blood oxygensaturation levels of a user. The blood oxygen monitor 314 may includeone or more light-emitting devices such as light-emitting diodes (LEDs).In some embodiments, the heart rate monitor 312 and blood oxygen monitor314 are combined into a single device.

The breath rate sensor 316 may be used to measure the breathing rate ofa user. The breath rate sensor 106 may include motion sensors and/oroptical sensors. In some embodiments, the breath rate sensor 316 mayhelp to indicate health and/or stress levels of a user.

The EDA sensor 317 may be used to measure the conductive properties ofskin. In some embodiments, skin conductance may be correlated with theproduction of sweat glands. In some cases, elevated production of sweatmay show stress or an increased response to stimuli. The EDA sensor 317may be configured to contact an extremity of the user, such as a part ofthe head, arm, or neck.

The thermometer 318 may be any commercially available or customthermometer configured to measure the temperature of a user. In someembodiments, the thermometer 318 is configured to measure the skintemperature of a user. In some embodiments, skin temperature may becorrelated to stress levels.

The communications link 320 of the biometric measurement device 300 maybe operable to transmit and receive biometric measurement data andanalysis. In some embodiments, the communications link 320 may beconfigured to communicate with local and remote networks, such as thecloud network 170 of FIG. 1. The communications link may be configuredto transmit and receive wireless communications such as WiFi andBluetooth signals. Alternatively or additionally, it can have a wiredconnection to a workstation, such as to collect data on a periodic basissuch as overnight while being charged in a docking station.

The biometric measurement device 300 may be configured to include orcommunicate with one or more of an electro-cardiogram (EKG) system 330,a functional magnetic resonance imaging (FMRI) system 340, and a facialexpression recognition system 350. The EKG system 330 may includeelectrodes placed on a user's body that measure electrical activity ofthe heart. The EKG system 330 may include a miniaturized processor aswell as other components and may be configured to be used by a customerservice center agent.

The FMRI system 340 may be used to measure brain activity by monitoringblood flow throughout the body and brain. The FMRI system may include anumber of devices that are attached to the user. In some embodiments,circulatory system measurements are received by a sensor system and FMRIdata is inferred from this data. In some embodiments, the FMRI system isin communication with the biometric measurement device 300 via a wiredor wireless connection.

The facial expression recognition system 350 may be used to identify thefacial expressions of a user. In some embodiments, the facial expressionrecognition system 350 includes one or more cameras that record thefacial expressions and posture of a user throughout a time period. Insome embodiments, the facial recognition system 350 is in communicationwith a database such as storage component 280 of FIG. 2. The databasemay include instructions related to detecting facial features and/oridentifying facial expressions. In some embodiments, the facialexpression recognition system 350 may be a geometric feature basedsystem. In this case, the facial expression recognition system 350 mayidentify major face components and/or feature points from imagescollected by the system 350. Furthermore, the distances between themajor face components and/or feature points may be calculated by thesystem 350 to identify facial expressions. In some embodiments, imagesor video collected by the facial expression recognition system 350 aretransmitted to an outside source, such as an external analysis system,for recognition and analysis. The posture and facial expressions of auser may be used to indicate an emotional state, and in some cases, astress level.

An exemplary method 400 of receiving biometric measurements and routingcommunications according to the disclosure is described with respect toFIG. 4. Method 400 may be performed by an analysis device such as theanalysis control system 200 of FIG. 2.

At step 402, the method 400 may include receiving a communication. Insome embodiments, the communication is received by an analysis system100 such as that depicted in FIG. 1. The communication may be or mayinclude any kind of internet-based interaction, video-based interactionand/or telephone-based interaction. The communication may include bothverbal and nonverbal data. Some or all of the communication may beconverted into a digital format. In some embodiments, the communicationis received by a customer service center and is directed to an agent.

At step 404, the method 400 may include routing the communication to anagent using a routing algorithm. The routing algorithm may be configuredto route the communication based on a number of factors, includingrelative workloads of various agents, skill sets of the agents, type ofcommunication, urgency, existing relationships with agents, and otherfactors. In some embodiments, the routing algorithm may be configured totake into account biometric measurements of the agents. For example,communications may be routed to an agent whose biometric measurementsindicate that he or she has a low stress level and/or has a high levelof empathy. In other embodiments, the routing recommendations providefor communications from a particular personality type to be routed to anagent that can best handle that personality type while minimizing oravoiding an increase in stress, and in some embodiments, lowering thestress of the agent. In other embodiments, the agent and customer willhave the same or another complementary personality type configuration,i.e., the agent's personality type is factored into the routingrecommendation along with the customer's or a predicted customer. In allthese embodiments, the level of agent empathy generally, or to aparticular customer personality type, may be an input factor in therouting recommendation.

At step 406, the method 400 may include activating biometric sensors.These biometric sensors may include sensors that collect biometricinformation from a user. In some embodiments, the biometric sensors mayinclude the biometric measurement device 180 as depicted in FIG. 1 orthe biometric measurement device 300 as depicted in FIG. 3. In someembodiments, some or all of the biometric sensors may be included on awearable device such as a wristband. In some embodiments, the biometricsensors may be activated before a communication is routed to the agent.For example, biometric sensors may be activated throughout a work day toprovide ongoing monitoring of an agent. Furthermore, the measurementscollected during the handling of two or more different communicationsmay be compared to provide analysis of the agent's performance. Ongoingmonitoring may also provide a comparison of biometric measurementsduring down times (which may serve as a baseline) and periods duringwhich the agent is working. This may help to determine stress levelsthroughout the work day.

At step 408, the method 400 may include conducting biometric testing ofthe agent using the biometric sensors. In some embodiments, thebiometric sensors are activated during the time that an agent receivesand interacts with the communication, such as responding to a phonecall, VoIP call, videoconference or video chat, or the like. Thebiometric sensors may also collect data during interactions between theagents and others, such as clients and other agents. The biometricsensors may be configured to assess the performance of the agent whilecompleting a task. The biometric testing may include collectingbiometric measurements such as blood pressure, heart rate, heart ratevariability, blood oxygen levels, breath rate, electrocardiogram (EKG)readings, functional magnetic resonance imaging (FMRI) readings, skintemperature, skin conductance, facial expressions, and othermeasurements. The biometric measurements received from the biometrictesting may be sent to an analysis system for analysis.

At step 410, the method 400 may include analyzing biometricmeasurements. This analysis may include correlating biometricmeasurements collected during the biometric testing of step 408 to alevel of performance, a level of health, or a level of empathy. Forexample, the biometric testing of step 408 may include gathering videoor images from a camera that show an agent's face during an interactionbetween the agent and a client. The video or images may be analyzed byan analysis system such as the analysis control center 160 of FIG. 1,and the analysis system may identify a number of facial expressionsduring the interaction, including “frustration”, “confusion”, and“anger.” These analysis results may be recorded by various components ofthe system. Furthermore, the analysis results may be correlated with aheightened level of stress and a lowered level of empathy for the agent.

At step 420, the method 400 may include setting empathy parameters. Insome embodiments of the present disclosure, the biometric measurementsmay be correlated with an empathy measurement or score of an agent.Although the term “empathy” may include a number of emotional responses,“empathy” as described herein may include one or more of the eightconceptualizations from C. D. Batson as noted by David Lester Neumannand Rae Westbury in “The Psychophysiological Measurement of Empathy”(2011), which is hereby incorporated by reference in its entirety. Theseconceptualizations include: (1) knowing another person's cognitive andaffective internal state, (2) adopting the posture or matching theneural response of another, (3) feeling as another person feels, (4)projecting oneself into another's situation, (5) imagining the thoughtsand feelings of another, (6) imagining how one would think and feel inthe other's place, (7) feeling distress at witnessing another'ssuffering, and (8) feeling for another person who is suffering. In someembodiments, people who show empathy, or who relatively show moreempathy than, e.g., another contact center agent, may communicate moreeffectively with others.

In some embodiments, empathy levels may be identified by the level ofemotional correlation between people that are communicating. Inparticular, a person exhibiting a relatively higher level of empathy mayexhibit very similar emotions to the person that they are communicatingwith. Accordingly, empathy parameters may include measuring andquantifying the emotions of the agent and as well as a person sendingthe communication. In the present disclosure, a contact is a personsending a communication which is received by the agent, or otherwiseparticipating in communication between the contact and agent. In somecases, the emotional state of the contact may be assessed by aspectssuch as voice volume, tone, word recognition, and linguistic analysis ofthe communication itself. The emotional states of the contact and theagent may then be compared to assess a level of correlation.

Measuring empathy may also include analysis of a number of biometricmeasurements. These may include any combination of neurological signals,mimicry, emotional contagion, feedback behavior, and physiologicalresponses to stimuli such as startle blinks and electrodermal activity,as well as other biometric measurements. Typically, without being boundby theory, the more measurements and more factors considered, the moreaccurate or certain the measurement.

In some embodiments, an agent may exhibit one or more neurologicalsignals that indicate empathy. These may include activity levels in theright putamen, the left posterior/middle insula, the anterior medialcingulated cortex and the left cerebellum that have been shown instudies, such as that by Gazzola, Aziz-Sadeh, and Keysers (2006), toshow a correlation to empathy. Furthermore, there may be correlationbetween empathetic behavior and high activity levels in areas of thebrain responsible for listening, such as the auditory cortex. In someembodiments, activity levels are measured by the FMRI system 340 of FIG.3. These activity measurements may be analyzed and correlated with analgorithm to determine an empathy level.

Mimicry may relate to similarities in the facial expressions and postureof people. For example, two people may exhibit mimicry by crossing theirarms while talking, lowering their voices at the same time, and smilingat each other. In some embodiments, mimicry may be related to highlistening and comprehension levels which may be strong signs of empathy.In some embodiments, mimicry is measured by identifying the posture andfacial expressions of the agent with the facial expression recognitionsystem 350 of FIG. 3. The facial expressions of the agent may becorrelated to the emotional state of a contact, for example by analyzinga video communication of the contact or analyzing changes in the tone ofthe contact during a telephone conversation. Mimicry may be furthermeasured by the correlation of vocal volume and tone of an agent to acontact while the agent and contact interact.

Emotional contagion and feedback behavior may refer to emotionalsimilarities between people engaged in an interaction. For example, anagent and a contact may be communicating by telephone. Both the agentand contact may exhibit happy emotions while talking about an upcomingholiday. The contact may mention that she is worried about a problemwith gifts for the holiday, and the agent may also express worry andsuggest a solution. At this point, the contact may thank the agent forhis suggestion with a contented tone. Similarly, the agent may expressthat he is happy to help. Accordingly, the high level of emotionalcontagion during the conversation may show that the agent is actingempathetically. Emotional contagion may be measured through analysis ofinteractions between agents and contacts including video and audiofeeds. Furthermore, incoming communications and responses may beanalyzed through linguistic analysis to measure emotional contagion. Forexample, the emotions of the agent and client may be shown by key wordsand phrases used, including “glad to help”, “hopefully”, and“regrettably”.

In some embodiments, exhibition of various physiological responses maybe correlated to a level of empathy. The physiological responses mayinclude startle blinks and electrodermal activity. A person may exhibitstartle blinks when subjected to startling or surprising stimuli.Startle blinks may also show that a person is paying attention to thestimuli, and may show that the person is listening intently. Sincepeople that are listening closely to other are more likely to beempathetic, startle blinks may be correlated to empathy levels. Startleblinks may be measured by the facial expression recognition system 350of FIG. 3.

Electrodermal activity (EDA) may be measured as changes in theelectrical properties of the skin, such as skin conductance. In someembodiments, skin conductance has been shown in to increase as moresweat is secreted from glands within the skin. An increase in sweatproduction may be correlated to a degree of emotional responsiveness andattentional engagement, and therefore to a level of empathy. In someembodiments, EDA is measured by the EDA sensor 317 depicted in FIG. 3.Other physiological responses may be measured by the various systems anddevices of the present disclosure. The empathy parameters of step 420may include any of the above measurements.

At step 422, the method 400 may include correlating biometric results toan empathy score. In some embodiments, the biometric measurements ofstep 410 are compared to the empathy parameters of step 420. In someembodiments, the empathy score shows the level of empathy of an agent.In particular, higher empathy scores may be attributed to moreempathetic behaviors. The empathy score may include sub-scores such aslistening, attentiveness, responsiveness, and emotional correlation.

At step 430, the method 400 may include setting performance parameters.In some embodiments, the performance parameters may be based on theefficiency of an agent, as well as the quality of the agent'sinteractions. Performance parameters may include response time, quantityand rate of interactions, and quality measurements, such as surveyscompleted by the agents, supervisors, and contacts.

At step 432, the method 400 may include creating a performance profilefor an agent. In some embodiments, the performance profile includes datafrom the biometric results of step 410 as well as the empathy score ofstep 422. The performance profile may relate to a single interaction, aswell as a series of interactions. In some embodiments, the performanceprofile may be used to judge the performance of the agent.

At step 434, the method 400 may include comparing the performanceprofile to the performance parameters. The results of this step may beused to assess the performance of the agent. In some embodiments, thehealth of the agent may be assessed at this step. For example, theperformance of an agent may be assessed during a work week. Toward theend of the week, the agent may show a significant drop in performance aswell as a number of negative biometric measurements, such as an elevatedheart rate and an increase in negative facial expressions. This maysignal that the agent has an elevated stress level. Appropriate actionmay be taken by the system or the agent's supervisor to decreaseworkload or adjust the type of communications being routed to the agent.Another suitable action is that the system is configured to provideprompts to better coach the agent, the supervisor, or both, to minimizehealth risks or issues, increase health outcomes, increase agentperformance while avoiding an increase in agent health risks or issues,or increase health outcomes while increasing agent performance.

The methods, apparatuses, and systems described herein may optionallyalso analyze comments based in part on the one or more biometricmeasurements that are provided by a coach relating to an agent'sinteraction with a customer. By way of example, the methods herein canreceive a coaching comment regarding an agent's interaction with acustomer, apply at least one scoring algorithm to the comment, andoutput a score of the scoring algorithm such as for the coach. During anin-person coaching meeting, for example, potential deficiencies in anagent's skill set can be identified, thereby leading to the assignmentof various learning or training exercises or performance goals. Goalsalso can be assigned during a coaching meeting with any assignedlearning and goals being annotated on a coaching form. In someembodiments, an agent can be given an opportunity to provide feedback onthe coaching session using the coaching form. In some embodiments, acoaching session is considered complete when the corresponding coachingform is annotated as such by the relevant coach. In some embodiments,however, the coaching session may not be deemed complete until furtheranalysis is undertaken in order to determine whether the coachingsession has resulted in one or more improvements in agent performance.

At least one scoring algorithm can be applied to each comment made bythe coach, either in-person or electronically. The scoring algorithmlooks for: (1) specific terms and phrases that indicate thecharacteristic or property desired (e.g., customization, action ability,and/or encouragement), (2) the density of those terms in the overallcomment; and (3) the presence of those terms in the first sentence ofthe comment. In certain embodiments, terms and phrases that are presentin the first sentence of a coaching session, or in each section of acoaching session (e.g., covering different goals or topics liketeamwork, efficiency, reliability, responsiveness, etc.) are givenheavier weight than those in the rest of the comment.

In various embodiments, these terms, phrases, or keywords are stored ina library or libraries that are accessed by a control system or ananalytics system. The library may separate the keywords, terms, andphrases into different categories. Keywords are the words previouslydetermined to indicate the specific characteristic of the coachingcomment. Each keyword may have respective aliases, which are essentiallysynonyms of keywords. Synonyms of the keywords may be identified andalso stored in the library. The aliases are typically treated asinterchangeable with the keywords from a scoring perspective, but in oneembodiment aliases can be treated as not interchangeable if specificwords, terms, or phrases are expected to be used. Also, due to theflexibility of the methods described herein, additional words, terms,and/or phrases may be added to the library at any time. For example,when it becomes apparent that another word is used frequently and isjust as effective as the associated keyword, the library may be updatedto include this word as an acceptable alias.

The scoring algorithm can be configured to detect keywords, terms, andphrases in the statements of the coach to the agent and the comments arescored based on the number of word hits in this embodiment. In oneembodiment, the scoring algorithm includes a “customized” algorithm thatlooks for words that identify the specific impact that a change inbehavior will have on future customer interactions and the agent'smetrics. For instance, the phrases “resulting in,” “help to increase,”“goal is to,” “saved a couple of seconds of talk time,” “to decreasecall length,” “consequently,” “as might be expected,” “due to,” “leadsto,” “brought about,” “was responsible for,” “to increase efficiency,”“we want to decrease/increase,” and “could haveincreased/decreased/produced/improved/saved/minimized” indicate theproperty of customization. In another embodiment, the scoring algorithmincludes an “actionable” algorithm that looks for words that identifybehavior that needs to be improved and language that is clearlyindicative of what the agent needs to do next time. The “actionable”algorithm also evaluates the proximity of action words to other actionwords. The more action words used, the closer they are together, and themore clearly indicated the next course of action is, the higher thecomment scores with the algorithm. Examples of “actionable” termsinclude “in the future,” “make sure to,” “need to work on,” “rememberto,” and “an opportunity to.” In yet another embodiment, the scoringalgorithm includes an “encouragement” algorithm that looks for wordsthat identify positive language that reinforces good behavior. Exemplarywords, terms, and phrases that the algorithm searches for include“appreciate,” “thanks,” “thank you,” “good/great/wonderful job,” and“keep up the good work.”

A scoring algorithm(s) is typically created by linguistic analysts andtypically trained using previously analyzed coaching comments. Eachalgorithm is trained with known inputs and learns these patterns throughone or more statistical methods. The algorithms can then properlyclassify new input based on the inputs it has received and processedduring training. The algorithm should be able to perform accurately onnew, unseen examples after having trained on a learning data set. Thelarger the comparable data set, the higher the accuracy the algorithm islikely to achieve. The feedback and scoring related to coaching commentscan advantageously be used to provide better comments in futurecoaching, or training of supervisors providing such coaching comments.In various embodiments, the algorithms are calibrated, customized, andupdated according to different coaching styles. Additional embodimentsdirected to providing coaching comments, or prompts, are disclosed inco-pending U.S. patent application Ser. No. 13/912,918, filed Jun. 7,2013, the entire contents of which is incorporated herein by expressreference thereto.

At step 436, the method 400 may include displaying the comparison ofstep 434 to a user. In some embodiments, the comparison is displayed tothe agent as a form of feedback information. The comparison may beaccompanied with a recommendation for improving performance duringinteractions. The comparison may be sent to a supervisor, other agents,and/or an agent database. In some embodiments, the comparison isdisplayed on a display device such as display 190 of FIG. 1 or displaycomponent 292 of FIG. 2.

At step 438, the method 400 may include the updating the routingalgorithm with the comparison. In some embodiments, the routingalgorithm is continuously updated with performance information from theagents. This may help to most efficiently route communications, as wellas to improve agent wellbeing. For example, actions may be taken toimprove the performance of the overstressed agent discussed in referenceto step 438, such as decreasing the amount of communications routed tothe agent or routing more positive communications to the agent. In someembodiments, the method 400 may repeat itself after step 438, forexample, beginning at step 402.

An exemplary method 500 of receiving biometric measurements of an agentand providing recommendations based on the biometric measurementsaccording to the disclosure is described with respect to FIG. 5. Method500 may be performed by an analysis system such as the analysis controlsystem 200 of FIG. 2.

At step 502, the method 500 may include receiving a communication. Insome embodiments, the communication is received by an analysis systemsuch as analysis system 100 of FIG. 1. The communication may be any kindof internet-based interaction, video-based interaction and/ortelephone-based interaction. The communication may include both verbaland nonverbal data. Some or all of the communication may be convertedinto a digital format. In some embodiments, the communication isreceived by a customer service center and is directed to one or moreagents.

At step 504, the method 500 may include routing the communication to anagent using a routing algorithm. The routing algorithm may be configuredto route the communication based on a number of factors, includingrelative workloads of the agents, skill sets of the agents, type ofcommunication, urgency, existing relationships with agents, and otherfactors. In some embodiments, the routing algorithm may be configured totake into account biometric measurements of agents. For example,communications may be routed to an agent whose biometric measurementsindicate that he or she has a low stress level.

At step 506, the method 500 may include activating biometric sensors.These biometric sensors may include sensors that collect biometricinformation from a user. In some embodiments, the biometric sensors mayinclude the biometric measurement device 180 as depicted in FIG. 1 orthe biometric measurement device 300 as depicted in FIG. 3. Some or allof the biometric sensors may be included on a wearable device such as awristband.

At step 508, the method 500 may include conducting biometric testing ofan agent using the biometric sensors. In some embodiments, the biometricsensors are activated during the time that an agent interacts with thecommunication. The biometric sensors may also be activated before thecommunication is routed to the agent. For example, the biometric sensorsmay provide ongoing measurement throughout a work day, including downtime and periods when the agent is responding to communications. Thebiometric sensors may also collect data during interactions between theagents and others, such as clients and other agents. The biometricsensors may be configured to assess the performance of the agent whilecompleting a task. In particular, the biometric testing may includecollecting biometric measurements such as blood pressure, heart rate,heart rate variability, breath rate, blood oxygen levels,electrocardiogram (EKG) readings, functional magnetic resonance imaging(FMRI) readings, skin temperature, skin conductance, facial expressions,and other measurements. The biometric measurements received from thebiometric testing may be sent to an analysis system for analysis.

At step 510, the method 500 may include analyzing the biometric results.This step may include collecting biometric measurements from the variousbiometric sensors and comparing them. The analysis may includecorrelating biometric measurements collected during the biometrictesting of step 508 to the wellbeing of the agent. For example,biometric measurements of an agent may be collected during a work day.An elevated heart rate, low blood oxygen levels, and high skinconductance may be measured during the end of the day. These biometricmeasurements may show that the agent is stressed.

At step 520, the method may include setting health parameters. In someembodiments, health parameters may include targets to compare thebiometric measurements to. For example, the health parameters mayinclude a resting heart rate of 70 beats per minute and a blood pressureof 120/80. In some embodiments, the health parameters may be set toreflect a base line for each of the biometric measurements.

At step 522, the method 500 may include comparing the biometric resultsof 510 to the health parameters of step 520 to create a health score.The health score may reflect the overall health of an agent as well astemporary health states. For example, the health score of an agent maystate that he has good overall health (for example, based on heart rate,pulse rate, and blood oxygen levels), but is currently exhibitingsignals of tension and stress (for example, based on skin conductanceand facial expression analysis). The health score may be compared tobase line health scores as well as being compared to the health scoresof other agents.

At step 524, the method 500 may include creating a recommendation toimprove the health score. In some embodiments, the recommendation ismade to correct one or more negative biometric measurements. Therecommendations may also include prompts to improve the agent's basichealth level, coaching prompts to reduce stress levels, and/or promptsfor more successfully interacting with others or responding tocommunications. Prompts to improve the agent's health may be directed toimproving one or more biometric results. For example, an agent may showa high blood pressure reading and a high heart rate variability duringseveral interactions. A recommendation may be sent to the agent withinstructions to take a break. The biometric measurements of the agentmay be recorded after the break and compared with earlier measurementsto ascertain whether stress levels have improved. The recommendationsmay also instruct the agent to adjust one or more biometric measurementdevices, for example, adjusting a heart rate monitor to obtain a clearerreading. The recommendation may be communicated to others such as theagent's supervisor. The recommendation may also include prompts to helpthe agent interact more successfully with other individuals. Forexample, the agent may receive a communication from an individual who isunhappy and difficult to work with, causing the measured stress level ofthe agent to rise. A recommendation after the communication may includeprompts on how to more effectively handle difficult communications inthe future along with a recommendation to go for a short walk. As theexamples show, the recommendation may include several types of promptsand may change over time to modify, e.g., improve the health and/orperformance of the agent. As used herein, the term “prompt(s)” isintended to include coaching advice, tips, feedback, or a combinationthereof, to (i) one or more supervisors to coach one or more contactagents, e.g., in person or electronically; (ii) directly to one or morecontact agent(s), e.g., automated coaching; or a combination thereof.

At step 530, the method 500 may include setting empathy parameters.These parameters may be related to one or more physical manifestationsof empathy, such as those discussed in reference to step 420 of method400. The empathy parameters may also include user defined parameters.For example, an agent may set goals and metrics for measuring empathylevels, such as setting a goal to listen more closely to contacts.

At step 532, the method 500 may include correlating the biometricresults of step 510 to the empathy parameters set in step 530 to createan empathy score. A higher empathy score may be attributed to moreempathetic behaviors. The empathy score may include sub-scores such aslistening, attentiveness, responsiveness, and emotional correlation.

At step 534, the method 500 may include creating a recommendation toimprove the empathy score. Examples of this recommendation may includean instruction to an agent to remove distractions to facilitate betterlistening and comprehension of communications. Because empathy levelsmay be correlated with health levels, the recommendation may alsoinclude health-related suggestions, such as getting something to eat ordrink, or taking a break. The recommendation may also include educationinformation about empathy. For example, the recommendation may includestatistics about empathy and common empathetic behaviors. In someembodiments, the recommendation is part of a game-based system designedto educate customer service center agents and others. The recommendationmay provide a personalized analysis of empathy, which may be presentedwith background information about empathy and empathetic behaviors.

At step 540, the method 500 may include updating the routing algorithm.In some embodiments, the routing algorithm may be updated to reflect thehealth and empathy recommendations created in steps 524 and 534,respectively. For example, a health recommendation may be createdsuggesting that the agent take a 30 minute break due to a high pulserate. The routing algorithm may be updated to prevent communicationsfrom being sent to the agent during the 30 minute break.

At step 542, the method 500 may include displaying the recommendationsto a user. The recommendations may be sent to the agent as well asothers, such as a supervisor, as well as to an agent database. In someembodiments, the recommendations are displayed on a display device suchas display 190 of FIG. 1 or display component 292 of FIG. 2. In someembodiments, the method 500 may repeat itself after step 542, forexample, beginning at step 502.

In view of the present disclosure, it will be appreciated that variousmethods, devices, computer readable media, and systems have beendescribed according to one or more embodiments for receiving biometricmeasurements of an agent and identifying relationships between thebiometric measurements, and the health and/or performance of the agent.These relationships may then be used to route communications to theagent and improve the performance and heath of the agent.

Where applicable, various embodiments provided by the present disclosuremay be implemented using hardware, software, or combinations of hardwareand software. Also where applicable, the various hardware componentsand/or software components set forth herein may be combined intocomposite components comprising software, hardware, and/or both withoutdeparting from the spirit of the present disclosure. Where applicable,the various hardware components and/or software components set forthherein may be separated into sub-components comprising software,hardware, or both without departing from the spirit of the presentdisclosure. In addition, where applicable, it is contemplated thatsoftware components may be implemented as hardware components, andvice-versa.

Software in accordance with the present disclosure, such as program codeand/or data, may be stored on one or more computer readable mediums. Itis also contemplated that software identified herein may be implementedusing one or more general purpose or specific purpose computers and/orcomputer systems, networked and/or otherwise. Where applicable, theordering of various steps described herein may be changed, combined intocomposite steps, and/or separated into sub-steps to provide featuresdescribed herein.

The various features and steps described herein may be implemented assystems comprising one or more memories storing various informationdescribed herein and one or more processors coupled to the one or morememories and a network, wherein the one or more processors are operableto perform steps as described herein, as non-transitory machine-readablemedium comprising a plurality of machine-readable instructions which,when executed by one or more processors, are adapted to cause the one ormore processors to perform a method comprising steps described herein,and methods performed by one or more devices, such as a hardwareprocessor, user device, server, and other devices described herein.

The foregoing outlines features of several embodiments so that a personof ordinary skill in the art may better understand the aspects of thepresent disclosure. Such features may be replaced by any one of numerousequivalent alternatives, only some of which are disclosed herein. One ofordinary skill in the art should appreciate that they may readily usethe present disclosure as a basis for designing or modifying otherprocesses, systems, and structures for carrying out the same purposesand/or achieving the same advantages of the embodiments introducedherein. One of ordinary skill in the art should also realize that suchequivalent constructions do not depart from the spirit and scope of thepresent disclosure, and that they may make various changes,substitutions and alterations herein without departing from the spiritand scope of the present disclosure.

The Abstract at the end of this disclosure is provided to allow a quickdetermination of the nature of the technical disclosure. It is submittedwith the understanding that it will not be used to interpret or limitthe scope or meaning of the claims.

What is claimed is:
 1. A computer-implemented method of routing acommunication with a customer in a customer service center, whichcomprises: routing a plurality of customer communications to a customerservice agent; activating an electronic wristband comprising a biometricsensor, the electronic wristband being associated with the agent whenthe communications are routed to the agent; measuring biometric data, bythe biometric sensor, associated with the agent during thecommunications; applying a linguistic-based psychological behavioralmodel to each of the communications to determine a personality type ofeach customer; receiving, by a processor, the measured biometric datafor the agent and the personality type of each customer; creating abiometric analysis based on comparing the measured biometric data to aplurality of biometric data targets; determining a performance scorebased on the agent's performance in interacting with each customerduring the communications, the performance score comprising responsetime, quantity of interactions, rate of interactions, and quality surveyresults; setting at least one empathy parameter; correlating themeasured biometric data to the at least one empathy parameter to createan empathy score; comparing the empathy score to the performance score;providing an empathy recommendation based on a comparison of the empathyscore to the performance score, wherein the empathy recommendation isbased on increasing the empathy score; updating a routing recommendationfor a future communication with a customer based on the empathyrecommendation such that the future communication is routed to an agenthaving a higher empathy score for a personality type of the customerthan other selected agents; and routing the future communication basedon the updated routing recommendation.
 2. The method of claim 1, whereinthe measured biometric data include one or more of a blood pressure, aheart rate, a heart rate variability, a blood oxygen level, anelectrocardiogram (EKG) reading, a skin temperature, and a skinconductance.
 3. The method of claim 1, which further comprisesdisplaying a performance score to a user.
 4. The method of claim 1,which further comprises displaying the routing recommendation to a user.5. The method of claim 1, which further comprises distributing therouting recommendation to a contact center for routing a customer to anagent during one or more future communications.
 6. The method of claim1, further comprising correlating the empathy score to a health score ofthe agent.
 7. The method of claim 1, further comprising determining astress level of the agent from comparing the measured biometric data tothe plurality of biometric data targets.
 8. The method of claim 7,wherein the measured biometric data includes a blood pressure and aheart rate, and the plurality of biometric data targets include aresting heart rate of 70 beats per minute and a blood pressure of120/80.
 9. The method of claim 7, wherein the updated routingrecommendation is further based on the stress level of the agent. 10.The method of claim 1, further comprising: determining a personalitytype of the agent; and comparing the personality type of the agent tothe personality type of the customer in the future communication,wherein the updated routing recommendation is further based on thecomparison of personality types.
 11. A computer-implemented method forcreating recommendations to route a future communication to a contactcenter agent, which comprises: routing one or more customercommunications with a customer to the agent; activating an electronicwristband comprising a biometric sensor, the electronic wristband beingassociated with the agent when the communications are routed to theagent; measuring biometric data, by the biometric sensor, associatedwith the agent during the communications; applying a linguistic-basedpsychological behavioral model to each of the communications todetermine a personality type of each customer; receiving, by aprocessor, the measured biometric data for the agent and the personalitytype of each customer; determining a performance score based on theagent's performance in interacting with each customer during thecommunications; setting at least one empathy parameter; correlating themeasured biometric data to the at least one empathy parameter to createan empathy score; comparing the empathy score to the performance score;providing an empathy recommendation based on a comparison of the empathyscore to the performance score, wherein the empathy recommendation isbased on increasing the empathy score; and updating a routingrecommendation for a future communication with a customer based on theempathy recommendation such that the future communication is routed toan agent having a higher empathy score for a personality type of thecustomer than other selected agents.
 12. The method of claim 11, whichfurther comprises determining a health score based on the biometricdata.
 13. The method of claim 12, wherein the health score includes astress level assessment, an overall health assessment, or both.
 14. Themethod of claim 11, wherein the biometric data includes one or more of ablood pressure, a heart rate, a heart rate variability, a blood oxygenlevel, an electrocardiogram (EKG) reading, a skin temperature, and askin conductance.
 15. The method of claim 11, further comprisingcorrelating the empathy score to a health score of the agent.
 16. Asystem to modify performance of contact center agents based on biometricmeasurements, which comprises: an electronic wristband comprising abiometric sensor configured to measure one or more biometricmeasurements of a contact center agent; an analysis processor incommunication with the electronic wristband, wherein the analysisprocessor is operably connected to a non-transitory computer readablemedium which comprises a plurality of instructions stored in associationtherewith that are accessible to, and executable by, the analysisprocessor, wherein the plurality of instructions when executed: receive,by a processor, the one or more biometric measurements from theelectronic wristband comprising the biometric sensor during a pluralityof communications with a customer; apply a linguistic-basedpsychological behavioral model to each of the plurality ofcommunications to determine a personality type of each customer;determine a performance score based on the agent's performance ininteracting with each customer during the communications; set at leastone empathy parameter; correlate the measured biometric data to the atleast one empathy parameter to create an empathy score; compare theempathy score to the performance score; provide an empathyrecommendation based on a comparison of the empathy score to theperformance score, wherein the empathy recommendation is based onincreasing the empathy score; update a routing recommendation for afuture communication with a customer based on the empathy recommendationsuch that the future communication is routed to an agent having a higherempathy score for a personality type of the customer than other selectedagents; and route the future communication based on the updated routingrecommendation.
 17. The system of claim 16, further comprising a displaydevice configured to display the one or more biometric measurements to auser.
 18. The system of claim 16, wherein the one or more biometricmeasurements include one or more of a blood pressure, a heart rate, aheart rate variability, a blood oxygen level, an electrocardiogram (EKG)reading, a skin temperature, and a skin conductance.
 19. The system ofclaim 16, wherein the biometric sensor includes one or more of a heartrate monitor, a blood oxygen monitor, an electrodermal analysis (EDA)sensor, a thermometer, an EKG system, and a functional magneticresonance imaging (FMRI) system.
 20. The system of claim 16, wherein theplurality of instructions further comprise instructions that, whenexecuted, correlate the empathy score to a health score of the agent.